Sustainable Practices in Global Supply Chains of Chinese Enterprises: Biblometeric Approach
Bibliographic record
Abstract
Chinese enterprises have indeed recognized the importance of sustainable practices in their global supply chains, with one key practice being the enhancement of supply chain transparency. These enterprises are implementing measures to trace and track raw materials and components, ensuring compliance with sustainability standards and ethical sourcing practices. This transparency is crucial in identifying and mitigating environmental and social risks within the supply chain. However, it is important to note that there is still a lack of extensive research in the context of China regarding sustainable practices in global supply chains. While some studies and initiatives have been conducted, there is a need for more comprehensive research to understand the specific challenges and opportunities faced by Chinese enterprises in adopting and implementing sustainable practices throughout their supply chains. The objective of this study is investigating the research progress on issue related Sustainable Practices in Global Supply Chains of Chinese Enterprises. In doing so, systematic literature research was implemented on the supply chains of Chinese enterprises' foreign direct investment (FDI) to provides insights into the penetration and significance of sustainable concepts in this topic. This paper utilizes advanced data visualization techniques and an in-depth literature review to comprehensively summarize and review previous research extracted from the Web of Science database. The study included 518 articles and analyzed them through RStudio and VOSviewer software. Research analysis reveals that most of the past research articles on this topic primarily come from China, followed by large economies such as the United States and the United Kingdom. However, when ranked by influence, the order is Canada, the UK, and the US. Around 2020, collaborations between countries mainly occurred in Asian nations. China, enterprises, and FDI are currently the most popular keywords. The importance of sustainability in the research on FDI in Chinese enterprises has been verified through data analysis and theoretical review. Key terms related to sustainability, such as "carbon dioxide emissions, economic growth, and energy consumption", are expected to play a vital role in future research. Current theoretical studies confirm that integrating environmental, social, and economic goals (ESG) into supply chain operations can implement a sustainable philosophy for the entire product lifecycle in Chinese OFDI enterprises. Disseminating sustainable management principles in supply chains among Chinese OFDI companies can contribute to ESG sustainability goals, while also enhancing the long-term profitability of the companies themselves.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.026 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".